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BackgroundThe current surgical methods for managing incisions after nipple excision in breast reconstruction patients are limited. However, double purse-string suture (DPS) shows promise in the treatment of nipple excision. This study aimed to investigate the safety and aesthetic outcomes of DPS nipple reconstruction in early breast cancer patients who underwent endoscopic skin-sparing mastectomy (E-SSM) and breast reconstruction.MethodsWe retrospectively analyzed the clinical data of 87 early breast cancer patients with nipple excision who underwent E-SSM with breast reconstruction. According to the suture methods of nipple incision, all patients were divided into the spindle suture (SS) group, single purse-string suture (SPS) group, and DPS group, with SS and SPS groups combined as the traditional suture (TS) group. Then, we compared the groups’ differences in aesthetic outcomes, surgical safety, and oncological safety.ResultsA total of 87 patients with 88 breasts were enrolled in this study (SS n=17, SPS n=21, DPS n=50). Patients in the DPS group had significantly better nipple reconstruction satisfaction, Harris scale and any complications incidence than the TS group (all p

Spinal cord injury (SCI) can cause loss of sensory and motor function below the level of injury, posing a serious threat to human health and quality of life. One significant characteristic feature of pathological changes following injury in the nervous system is demyelination, which partially contributes to the long-term deficits in neural function after injury. The remyelination in the central nervous system (CNS) is mainly mediated by oligodendrocyte progenitor cells (OPCs). Numerous complex intracellular signaling and transcriptional factors regulate the differentiation process from OPCs to mature oligodendrocytes (OLs) and myelination. Studies have shown the importance of microRNA (miRNA) in regulating OPC functions. In this review, we focus on the demyelination and remyelination after SCI, and summarize the progress of miRNAs on OPC functions and remyelination, which might provide a potential therapeutic target for SCI treatments.

BackgroundOur center proposes a new technique that effectively provides space to broaden the surgical field of view and overcomes the limitations of endoscopy-assisted nipple-sparing mastectomy (E-NSM) by changing the dissection sequence and combining it with air inflation. The purpose of this study was to compare the clinical outcomes of the new technique designated “reverse-sequence endoscopic nipple-sparing mastectomy (R-E-NSM) with subpectoral breast reconstruction (SBR)“ and the conventional E-NSM (C-E-NSM) with SBR.MethodAll patients undergoing E-NSM with SBR at our breast center between April 2017 and December 2022 were included in this study. The cohort was divided into the C-E-NSM group and the R-E-NSM group. The operation time, anesthesia time, medical cost, complications, cosmetic outcomes, and oncological safety were compared.ResultsTwenty-six and seventy-nine consecutive patients were included in the C-E-NSM and R-E-NSM groups, with average ages of 36.9 ± 7.0 years and 39.7 ± 8.4 years (P=0.128). Patients in the R-E-NSM group had significantly shorter operation time (204.6 ± 59.2 vs. 318.9 ± 75.5 minutes, p

ObjectivesIn recent years, the desire to make a more fine-grained identification on mild cognitive impairment (MCI) has become apparent, the etiological diagnosis of MCI in particular. Nevertheless, new methods for the etiological diagnosis of MCI are currently insufficient. The objective of this study was to establish discriminative measures for amnestic mild cognitive impairment (a-MCI) and MCI caused by cerebral small vessel disease (CSVD).Materials and methodsIn total, 20 normal controls (NCs), 33 a-MCI patients, and 25 CSVD-MCI patients performed comprehensive neuropsychological assessments concerning global cognitive function and five cognitive domains as well as magnetic resonance imaging scan with diffusion tensor imaging (DTI). Diffusion parameters including fractional anisotropy and mean diffusivity of 20 major white matter metrics were obtained by ROI-based analyses. The neuropsychological tests and diffusion measurements were compared and binary logistic regression was used to identify the best differential indicator for the two MCI subgroups. The discriminating power was calculated by receiver operating characteristic analysis.ResultsAmnestic mild cognitive impairment group showed significant impairment in memory and language function, while CSVD-MCI group revealed more deficits in multi-cognitive domains of memory, language, attention and executive function than controls. Compared to the a-MCI, CSVD-MCI was significantly dysfunctional in the executive function. The CSVD-MCI group had decreased fractional anisotropy and increased mean diffusivity values throughout widespread white matter areas. CSVD-MCI presented more severe damage in the anterior thalamic radiation, forceps major, forceps minor and right inferior longitudinal fasciculus compared with a-MCI group. No significant neuropsychological tests were found in the binary logistic regression model, yet the DTI markers showed a higher discriminative power than the neuropsychological tests. The Stroop test errors had moderate potential (AUC = 0.747; sensitivity = 76.0%; specificity = 63.6%; P = 0.001; 95% CI: 0.617–0.877), and the mean diffusivity value of forceps minor demonstrated the highest predictive power to discriminate each MCI subtype (AUC = 0.815; sensitivity = 88.0%; specificity = 72.7%; P < 0.001; 95% CI: 0.698–0.932).ConclusionThe mean diffusivity of forceps minor may serve as an optimal indicator to differentiate between a-MCI and CSVD-MCI.

Traditional Chinese medicine (TCM) usually acts in the form of compound prescriptions in the treatment of complex diseases. The herbs contained in each prescription have the dual nature of efficiency and toxicity due to their complex chemical component, and the principle of prescription is usually to increase efficiency and reduce toxicity. At present, the studies on prescriptions have mainly focused on the consideration of the material basis and possible mechanism of the action mode, but the quantitative research on the compatibility rule of increasing efficiency and reducing toxicity is still the tip of the iceberg. With the extensive application of computational pharmacology technology in the research of TCM prescriptions, it is possible to quantify the mechanism of synergism and toxicity reduction of the TCM formula. Currently, there are some classic drug pairs commonly used to treat complex diseases, such as Tripterygium wilfordii Hook. f. with Lysimachia christinae Hance for lung cancer, Aconitum carmichaelii Debeaux with Glycyrrhiza uralensis Fisch. in the treatment of coronary heart disease, but there is a lack of systematic quantitative analysis model and strategy to quantitatively study the compatibility rule and potential mechanism of synergism and toxicity reduction. To address this issue, we designed an integrated model which integrates matrix decomposition and shortest path propagation, taking into account both the crosstalk of the effective network and the propagation characteristics. With the integrated model strategy, we can quantitatively detect the possible mechanisms of synergism and attenuation of Tripterygium wilfordii Hook. f. and Lysimachia christinae Hance in the treatment of lung cancer. The results showed the compatibility of Tripterygium wilfordii Hook. f. and Lysimachia christinae Hance could increase the efficacy and decrease the toxicity of lung cancer treatment through MAPK pathway and PD-1 checkpoint pathway in lung cancer.

ObjectiveTo compare and evaluate radiomics models to preoperatively predict β-catenin mutation in patients with hepatocellular carcinoma (HCC).MethodsNinety-eight patients who underwent preoperative gadobenate dimeglumine (Gd-BOPTA)-enhanced MRI were retrospectively included. Volumes of interest were manually delineated on arterial phase, portal venous phase, delay phase, and hepatobiliary phase (HBP) images. Radiomics features extracted from different combinations of imaging phases were analyzed and validated. A linear support vector classifier was applied to develop different models.ResultsAmong all 15 types of radiomics models, the model with the best performance was seen in the RHBP radiomics model. The area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity of the RHBP radiomics model in the training and validation cohorts were 0.86 (95% confidence interval [CI], 0.75–0.93), 0.75, 1.0, and 0.65 and 0.82 (95% CI, 0.63–0.93), 0.73, 0.67, and 0.76, respectively. The combined model integrated radiomics features in the RHBP radiomics model, and signatures in the clinical model did not improve further compared to the single HBP radiomics model with AUCs of 0.86 and 0.76. Good calibration for the best RHBP radiomics model was displayed in both cohorts; the decision curve showed that the net benefit could achieve 0.15. The most important radiomics features were low and high gray-level zone emphases based on gray-level size zone matrix with the same Shapley additive explanation values of 0.424.ConclusionThe RHBP radiomics model may be used as an effective model indicative of HCCs with β-catenin mutation preoperatively and thus could guide personalized medicine.

PurposeTo establish an ensemble machine learning (ML) model for predicting the risk of futile recanalization, malignant cerebral edema (MCE), and cerebral herniation (CH) in patients with acute ischemic stroke (AIS) who underwent mechanical thrombectomy (MT) and recanalization.MethodsThis prospective study included 110 patients with premorbid mRS ≤ 2 who met the inclusion criteria. Futile recanalization was defined as a 90-day modified Rankin Scale score >2. Clinical and imaging data were used to construct five ML models that were fused into a logistic regression algorithm using the stacking method (LR-Stacking). We added the Shapley Additive Explanation method to display crucial factors and explain the decision process of models for each patient. Prediction performances were compared using area under the receiver operating characteristic curve (AUC), F1-score, and decision curve analysis (DCA).ResultsA total of 61 patients (55.5%) experienced futile recanalization, and 34 (30.9%) and 22 (20.0%) patients developed MCE and CH, respectively. In test set, the AUCs for the LR-Stacking model were 0.949, 0.885, and 0.904 for the three outcomes mentioned above. The F1-scores were 0.882, 0.895, and 0.909, respectively. The DCA showed that the LR-Stacking model provided more net benefits for predicting MCE and CH. The most important factors were the hypodensity volume and proportion in the corresponding vascular supply area.ConclusionUsing the ensemble ML model to analyze the clinical and imaging data of AIS patients with successful recanalization at admission and within 24 h after MT allowed for accurately predicting the risks of futile recanalization, MCE, and CH.

BackgroundImmunotherapy, adjuvant chemotherapy, and prognosis of colorectal cancer are associated with MSI. Biopsy pathology cannot fully reflect the MSI status and heterogeneity of rectal cancer.PurposeTo develop a radiomic-based model to preoperatively predict MSI status in rectal cancer on MRI.AssessmentThe patients were divided into two cohorts (training and testing) at a 7:3 ratio. Radiomics features, including intensity, texture, and shape, were extracted from the segmented volumes of interest based on T2-weighted and ADC imaging.Statistical TestsIndependent sample t test, Mann-Whitney test, the chi-squared test, Receiver operating characteristic curves, calibration curves, decision curve analysis and multi-variate logistic regression analysisResultsThe radiomics models were significantly associated with MSI status. The T2-based model showed an area under the curve of 0.870 with 95% CI: 0.794–0.945 (accuracy, 0.845; specificity, 0.714; sensitivity, 0.976) in training set and 0.895 with 95% CI, 0.777–1.000 (accuracy, 0.778; specificity, 0.887; sensitivity, 0.772) in testing set. The ADC-based model had an AUC of 0.790 with 95% CI: 0.794–0.945 (accuracy, 0.774; specificity, 0.714; sensitivity, 0.976) in training set and 0.796 with 95% CI, 0.777–1.000 (accuracy, 0.778; specificity, 0.889; sensitivity, 0.772) in testing set. The combined model integrating T2 and ADC features showed an AUC of 0.908 with 95% CI: 0.845–0.971 (accuracy, 0.857; specificity, 0.762; sensitivity, 0.952) in training set and 0.926 with 95% CI: 0.813-1.000 (accuracy, 0.852; specificity, 1.000; sensitivity, 0.778) in testing set. Calibration curve showed that the combined score had a good calibration degree, and the decision curve demonstrated that the combined score was of benefit for clinical use.Data ConclusionRadiomics analysis of T2W and ADC images showed significant relevance in the prediction of microsatellite status, and the accuracy of combined model of ADC and T2W features was better than either alone.

BackgroundPigmented villonodular synovitis (PVNS) is a rare condition that involves benign proliferation of the synovial tissue and is characterized by severe joint destruction and high recurrence even after surgical resection. However, poor understanding of the pathogenesis limits its effective therapy.MethodIn this study, gene expression profiles of six patients with PVNS, 11 patients with osteoarthritis (OA), nine patients with rheumatoid arthritis (RA) (E-MTAB-6141), and three healthy subjects (GSE143514) were analyzed using integrating RNA sequencing (RNA-seq) and microarray to investigate the PVNS transcriptome. Gene ontology, string, and cytoscape were used to determine the gene functional enrichment. Cell functional molecules were detected using flow cytometry or immunohistochemical test to identify the cell subset and function. CD14+ cells were isolated and induced to osteoclast to evaluate the monocyte/macrophage function.ResultsThe most obvious local manifestations of PVNS were inflammation, including increased immune cells infiltration and cytokine secretion, and tumor phenotypes. High proportion of inflammatory cells, including T cells, natural killer (NK) cells, NKT cells, and B cells were recruited from the blood. Th17 and monocytes, especially classical monocytes but not nonclassical monocytes, increased in PVNS synovium. An obvious increase in osteoclastogenesis and macrophage activation was observed locally. Elevated expression of MMP9, SIGLEC 15, and RANK were observed in myeloid cell of PVNS than OA. When compared with RA, osteoclast differentiation and myeloid cell activation are PVNS-specific characters, whereas T cell activation is shared by PVNS and RA.ConclusionThe transcriptional expression characteristics of PVNS showed increased immune response, cell migration, and osteoclastogenesis. Osteoclast differentiation is only observed in PVNS but not RA, whereas T-cell activation is common in inflammatory arthritis.

The p38 regulated/activated protein kinase (PRAK) is a protein kinase downstream of p38MAPK. The present study investigated its function in the macrophage. Myeloid-specific deletion of Prak resulted in a significant reduction in F4/80+CD11b+ peritoneal macrophages with decreased expression of MHC-II and CD80. Upon infection with Listeria monocytogenes, Prak-deficient mice demonstrated an increased mortality, which was accompanied by a higher bacterial load in multiple tissues and elevated levels of proinflammatory cytokines in the serum. While the Prak-deficient macrophage showed similar potency in phagocytosis assays, its bactericidal activity was severely impaired. Moreover, Prak deficiency was associated with defects in ROS production, inflammasome activation as well as autophagy induction. Therefore, PRAK critically contributes to the clearance of intracellular pathogens by affecting multiple aspects of the macrophage function.

To explore the evaluation of white matter structural network analysis in the differentiation of Alzheimer’s disease (AD) and subcortical ischemic vascular dementia (SIVD), 67 participants [31 AD patients, 19 SIVD patients, and 19 normal control (NC)] were enrolled in this study. Each participant underwent 3.0T MRI scanning. Diffusion tensor imaging (DTI) data were analyzed by graph theory (GRETNA toolbox). Statistical analyses of global parameters [gamma, sigma, lambda, global shortest path length (Lp), global efficiency (Eg), and local efficiency (Eloc)] and nodal parameters [betweenness centrality (BC)] were obtained. Network-based statistical analysis (NBS) was employed to analyze the group differences of structural connections. The diagnosis efficiency of nodal BC in identifying different types of dementia was assessed by receiver operating characteristic (ROC) analysis. There were no significant differences of gender and years of education among the groups. There were no significant differences of sigma and gamma in AD vs. NC and SIVD vs. NC, whereas the Eg values of AD and SIVD were statistically decreased, and the lambda values were increased. The BC of the frontal cortex, left superior parietal gyrus, and left precuneus in AD patients were obviously reduced, while the BC of the prefrontal and subcortical regions were decreased in SIVD patients, compared with NC. SIVD patients had decreased structural connections in the frontal, prefrontal, and subcortical regions, while AD patients had decreased structural connections in the temporal and occipital regions and increased structural connections in the frontal and prefrontal regions. The highest area under curve (AUC) of BC was 0.946 in the right putamen for AD vs. SIVD. White matter structural network analysis may be a potential and promising method, and the topological changes of the network, especially the BC change in the right putamen, were valuable in differentiating AD and SIVD patients.

Background: Hypothesis-driven functional connectivity (FC) analyses have revealed abnormal functional interaction of regions or networks involved in pain processing in episodic migraine patients. We aimed to investigate the resting-state FC patterns in episodic migraine by combining data-driven voxel-wise degree centrality (DC) calculation and seed-based FC analysis.Methods: Thirty-nine patients suffering from episodic migraine without aura and 35 healthy controls underwent clinical assessment and functional MRI. DC was analyzed voxel-wise and compared between groups, and FC of regions with DC differences were further examined using a seed-based approach.Results: Compared with the control group, the migraine group showed increased and decreased DC in the right posterior insula and left crus I, respectively. Seed-based FC analyses revealed that migraine patients demonstrated increased right posterior insula connections with the postcentral gyrus, supplementary motor area/paracentral lobule, fusiform gyrus and temporal pole. The left crus I showed decreased FC with regions of the default mode network (DMN), including the medial prefrontal cortex (mPFC), angular gyrus, medial and lateral temporal cortex in patients with migraine. Furthermore, pain intensity positively correlated with DC in the right amygdala/parahippocampal gyrus, and migraine frequency negatively correlated with FC between the left crus I and mPFC.Conclusion: Patients with episodic migraine without aura have increased FC with the right posterior insula and decreased FC within the DMN, which may underlie disturbed sensory integration and cognitive processing of pain. The left crus I-mPFC connectivity may be a useful biomarker for assessing migraine frequency.

In the literature on implicit learning, controversy exists regarding whether the knowledge obtained from implicit sequence learning consists of context-bound superficial features or context-free structural rules. To explore the nature of implicit knowledge, event related potentials (ERP) recordings of participants’ performances in a non-local dependent transfer task under two response-stimulus-interval (RSI) conditions (250 and 750 ms) were obtained. In the behavioral data, a transfer effect was found in the 750 ms RSI condition but not in the 250 ms RSI condition, suggesting that a long RSI is the basis for the occurrence of non-local dependent transfer, as which might have provided enough reaction time for participants to process and capture the implicit rule. Moreover, P300 amplitude was found to be sensitive to the impact of RSI on the training process (i.e., the longer RSI elicited higher P300 amplitudes), while variations in both N200 (i.e., a significant increase) and P300 amplitudes (i.e., a significant decrease) were found to be related to the presence of a transfer effect. Our results supported the claim that implicit learning can involve abstract rule knowledge acquisition under an appropriate RSI condition, and that amplitude variation in early ERP components (i.e., N200 and P300) can be useful indexes of non-local dependent learning and transfer effects.

Objective: To compare and evaluate radiomics models to preoperatively predict b-catenin mutation in patients with hepatocellular carcinoma (HCC). Methods: Ninety-eight patients who underwent preoperative gadobenate dimeglumine (Gd-BOPTA)-enhanced MRI were retrospectively included. Volumes of interest were manually delineated on arterial phase, portal venous phase, delay phase, and hepatobiliary phase (HBP) images. Radiomics features extracted from different combinations of imaging phases were analyzed and validated. A linear support vector classifier was applied to develop different models. Results: Among all 15 types of radiomics models, the model with the best performance was seen in the RHBP radiomics model. The area under the receiver operating characteristic curve (AUC), accuracy, sensitivity, specificity of the RHBP radiomics model in the training and validation cohorts were 0.86 (95% confidence interval [CI], 0.75–0.93), 0.75, 1.0, and 0.65 and 0.82 (95% CI, 0.63–0.93), 0.73, 0.67, and 0.76, respectively. The combined model integrated radiomics features in the RHBP radiomics model, and signatures in the clinical model did not improve further compared to the single HBP radiomics model with AUCs of 0.86 and 0.76. Good calibration for the best RHBP radiomics model was displayed in both cohorts; the decision curve showed that the net benefit could achieve 0.15. The most important radiomics features were low and high gray-level zone emphases based on gray-level size zone matrix with the same Shapley additive explanation values of 0.424. Conclusion: The RHBP radiomics model may be used as an effective model indicative of HCCs with b-catenin mutation preoperatively and thus could guide personalized medicine. [ABSTRACT FROM AUTHOR]

Malate dehydrogenases (MDHs) are key metabolic enzymes that play important roles in plant growth and development. In the present study, we isolated the full-length and coding sequences of BraMDH from Chinese cabbage [Brassica campestris L. ssp. pekinensis (Lour) Olsson]. We conducted bioinformatics analysis and a subcellular localization assay, which revealed that the BraMDH gene sequence contained no introns and that BraMDH is localized to the chloroplast. In addition, the expression pattern of BraMDH in Chinese cabbage was investigated, which revealed that BraMDH was heavily expressed in inflorescence apical meristems, as well as the effect of BraMDH overexpression in two homozygous transgenic Arabidopsis lines, which resulted in early bolting and taller inflorescence stems. Furthermore, the fresh and dry weights of aerial tissue from the transgenic Arabidopsis plants were significantly higher than those from the corresponding wild-type plants, as were plant height, the number of rosette leaves, and the number of siliques produced, and the transgenic plants also exhibited stronger aluminum resistance when treated with AlCl3. Therefore, our results suggest that BraMDH has a dramatic effect on plant growth and that the gene is involved in both plant growth and aluminum resistance. [ABSTRACT FROM AUTHOR]

A two-way Fano resonance switch in the plasmonic metamaterials has been proposed and experimentally demonstrated. The electrical Fano switch is composed of two concentric spoof localized surface plasmon (LSP) resonators. By adjusting the slit in the inner spoof LSP resonator, two different Fano resonance modes could be supported. By loading a Schottky barrier diode (SBD)across the slit in the inner LSP resonator, both Fano resonance modes can be simultaneously switched when the SBD is forward biased or reverse biased, and their switch status is opposite. Both simulated and measured results agree well at microwave frequencies and verify the two-way Fano resonance switch. The devices could be applied in many applications such as plasmonic circuits, multiway sensing or switching, and so on.